ChromaTOF Tile — The Fast-track to Chemical Insights

ChromaTOF Tile is an extremely effective tool for rapid comparisons of GCxGC data, designed to get labs from data to decisions faster than ever.

Tile efficiently compiles and reviews the raw GCxGC data to highlight differences between the samples or sets of samples. A variety of sample comparison options are available to accommodate different experimental designs and analysis objectives. Visualization and summary views like PCA and loading plots visually identify chemical features and classes, creating captivating publication figures.

Chemical differentiators are clearly defined for the analyst, aiding workflows including, but not limited to: Quality control (i.e. product failure analysis, raw material and final product screening), biomarker discovery, and differentiating sources or treatment groups.

Ready-to-Deliver Results

Image depicts Fisher Ratio concept: Four groups of four colored circles, arranged in a grid

Fisher Ratio

For data sets with defined groups and replicates, the Fisher Ratio test yields optimal results. Key chemical differentiators between the groups are surfaced, while intra-group variation is suppressed, so you can focus only on what’s important. Great for biomarker discovery, comparing ingredient sources, and more

Image depicts Coefficient Variation concept: Colored circles are in a homogenous group

Coefficient of Variation

For data sets without defined sample groups, the Coefficient of Variation test can help identify underlying chemical signatures that link or differentiate samples. Great first step for isolating meaningful traits from confounding variables, like in complex screening experiments, blinded data sets, and more.

Image depicts Fold Change concept: two colored dots are equally balanced on a scale

Fold Change

For data sets without replicates, the Fold Change test can expedite chemical insights. Great for instances where rapid results are the priority, like product failure analysis, off-odor identification, and more.

Tile in Action

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The Fisher Ratio test uses a chromatographic tiling approach to connect and compare data. Class-to-class variation is compared relative to “within class” variation. This test highlights differences between specific sample classes in data sets where other variation and differences are also expected. It’s best used for experiments where the analysis goals involve comparing different classes or groups of samples with each other.

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The Coefficient of Variation test uses a chromatographic tiling approach to connect and compare data. It finds differences by calculating the standard deviation across the sample set relative to the mean. It’s an efficient way to focus data analysis and quickly uncover information about your samples. This test is most effective when reviewing individual analytes and exploring chemical differences, especially when sample groups are unknown or unclear.

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The Fold Change test uses a chromatographic tiling approach to connect and compare data. This test can be performed with just two samples, making it perfect for direct comparisons. Raw data is rapidly compared to find the retention windows where there are differences between the samples. The Fold Change test is best used in experiments where you are looking for analytes that may relate to a cause in differentiation of a sample.
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Theory of Operation

LECO sought strategies to bypass the tedious task of manual GCxGC contour plot comparison, freeing analysts to pursue the next project or rapidly progress key research goals. Traditional peak finding and peak table filtering wouldn’t be fast enough, and couldn’t easily differentiate injection variability from real sample chemistry differences

ChromaTOF Tile Application Interface

In collaboration with Dr. Robert Synovec’s research team, LECO developed a region-based approach to identifying features in GCxGC contour plots. Raw MS data is segmented by “tiles” – small rectangles defined by retention times – and tiles with unique m/z fragments are identified in the samples. These tiles can then be rapidly compared with those in other samples, creating a heatmap of tile intensity that direct analysts’ attention to characteristic features of a sample or group of samples.

ChromaTOF Tile Application Interface featuring heatmaps

ChromaTOF Tile References

 

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